Overview

Brought to you by YData

Dataset statistics

Number of variables43
Number of observations448203
Missing cells9500980
Missing cells (%)49.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory141.1 MiB
Average record size in memory330.0 B

Variable types

Text34
Boolean2
Numeric3
Categorical2
Unsupported1
DateTime1

Alerts

Metadata Date has constant value "2017-04-03 08:00:08"Constant
Repository has constant value "Metropolitan Museum of Art, New York, NY"Constant
Department is highly overall correlated with Is Public Domain and 1 other fieldsHigh correlation
Is Public Domain is highly overall correlated with DepartmentHigh correlation
Object Begin Date is highly overall correlated with Object End DateHigh correlation
Object End Date is highly overall correlated with Object Begin DateHigh correlation
Object ID is highly overall correlated with DepartmentHigh correlation
Is Highlight is highly imbalanced (96.1%)Imbalance
Title has 31447 (7.0%) missing valuesMissing
Culture has 261685 (58.4%) missing valuesMissing
Period has 376321 (84.0%) missing valuesMissing
Dynasty has 425185 (94.9%) missing valuesMissing
Reign has 437386 (97.6%) missing valuesMissing
Portfolio has 427833 (95.5%) missing valuesMissing
Artist Role has 188294 (42.0%) missing valuesMissing
Artist Prefix has 359275 (80.2%) missing valuesMissing
Artist Display Name has 187092 (41.7%) missing valuesMissing
Artist Display Bio has 224139 (50.0%) missing valuesMissing
Artist Suffix has 437991 (97.7%) missing valuesMissing
Artist Alpha Sort has 187115 (41.7%) missing valuesMissing
Artist Nationality has 252071 (56.2%) missing valuesMissing
Artist Begin Date has 232969 (52.0%) missing valuesMissing
Artist End Date has 235378 (52.5%) missing valuesMissing
Object Date has 15594 (3.5%) missing valuesMissing
Medium has 8048 (1.8%) missing valuesMissing
Dimensions has 62843 (14.0%) missing valuesMissing
Geography Type has 389740 (87.0%) missing valuesMissing
City has 417683 (93.2%) missing valuesMissing
State has 439843 (98.1%) missing valuesMissing
County has 445715 (99.4%) missing valuesMissing
Country has 373753 (83.4%) missing valuesMissing
Region has 417125 (93.1%) missing valuesMissing
Subregion has 426487 (95.2%) missing valuesMissing
Locale has 433108 (96.6%) missing valuesMissing
Locus has 441264 (98.5%) missing valuesMissing
Excavation has 432684 (96.5%) missing valuesMissing
River has 446100 (99.5%) missing valuesMissing
Classification has 58279 (13.0%) missing valuesMissing
Rights and Reproduction has 425228 (94.9%) missing valuesMissing
Object Begin Date is highly skewed (γ1 = 667.3446274)Skewed
Object End Date is highly skewed (γ1 = 668.1311124)Skewed
Object ID has unique valuesUnique
Link Resource has unique valuesUnique
Period is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2025-10-23 23:13:46.558431
Analysis finished2025-10-23 23:14:27.268980
Duration40.71 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

Distinct445627
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2025-10-24T01:14:27.716169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length42
Median length39
Mean length10.917084
Min length3

Characters and Unicode

Total characters4893070
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique443051 ?
Unique (%)98.9%

Sample

1st row1979.486.1
2nd row1980.264.5
3rd row67.265.9
4th row67.265.10
5th row67.265.11
ValueCountFrequency (%)
burdick21130
 
4.1%
b20453
 
4.0%
3142462
 
0.5%
3071555
 
0.3%
2181498
 
0.3%
3271422
 
0.3%
3261162
 
0.2%
3241135
 
0.2%
2161009
 
0.2%
328979
 
0.2%
Other values (443731)462843
89.8%
2025-10-24T01:14:28.279510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.914909
18.7%
1624683
12.8%
2453240
9.3%
0386817
7.9%
3367422
7.5%
5318833
 
6.5%
9307966
 
6.3%
4302056
 
6.2%
6279204
 
5.7%
7235444
 
4.8%
Other values (71)702496
14.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)4893070
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.914909
18.7%
1624683
12.8%
2453240
9.3%
0386817
7.9%
3367422
7.5%
5318833
 
6.5%
9307966
 
6.3%
4302056
 
6.2%
6279204
 
5.7%
7235444
 
4.8%
Other values (71)702496
14.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4893070
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.914909
18.7%
1624683
12.8%
2453240
9.3%
0386817
7.9%
3367422
7.5%
5318833
 
6.5%
9307966
 
6.3%
4302056
 
6.2%
6279204
 
5.7%
7235444
 
4.8%
Other values (71)702496
14.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4893070
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.914909
18.7%
1624683
12.8%
2453240
9.3%
0386817
7.9%
3367422
7.5%
5318833
 
6.5%
9307966
 
6.3%
4302056
 
6.2%
6279204
 
5.7%
7235444
 
4.8%
Other values (71)702496
14.4%

Is Highlight
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size437.8 KiB
False
446344 
True
 
1859
ValueCountFrequency (%)
False446344
99.6%
True1859
 
0.4%
2025-10-24T01:14:28.336781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Is Public Domain
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size437.8 KiB
False
246004 
True
202199 
ValueCountFrequency (%)
False246004
54.9%
True202199
45.1%
2025-10-24T01:14:28.373650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Object ID
Real number (ℝ)

High correlation  Unique 

Distinct448203
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346272.87
Minimum1
Maximum750830
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 MiB
2025-10-24T01:14:28.442121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27323.1
Q1198808.5
median349816
Q3481764.5
95-th percentile705059.9
Maximum750830
Range750829
Interquartile range (IQR)282956

Descriptive statistics

Standard deviation206914.99
Coefficient of variation (CV)0.59754894
Kurtosis-0.89013797
Mean346272.87
Median Absolute Deviation (MAD)141705
Skewness0.13598044
Sum1.5520054 × 1011
Variance4.2813812 × 1010
MonotonicityStrictly increasing
2025-10-24T01:14:28.532818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7508301
 
< 0.1%
11
 
< 0.1%
21
 
< 0.1%
31
 
< 0.1%
41
 
< 0.1%
51
 
< 0.1%
61
 
< 0.1%
71
 
< 0.1%
81
 
< 0.1%
91
 
< 0.1%
Other values (448193)448193
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
7508301
< 0.1%
7508291
< 0.1%
7508281
< 0.1%
7508271
< 0.1%
7508261
< 0.1%
7508251
< 0.1%
7508241
< 0.1%
7508231
< 0.1%
7508221
< 0.1%
7508211
< 0.1%

Department
Categorical

High correlation 

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
Drawings and Prints
154445 
European Sculpture and Decorative Arts
42528 
Asian Art
36727 
Photographs
36258 
Costume Institute
33681 
Other values (15)
144564 

Length

Max length41
Median length38
Mean length19.431282
Min length9

Characters and Unicode

Total characters8709159
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAmerican Decorative Arts
2nd rowAmerican Decorative Arts
3rd rowAmerican Decorative Arts
4th rowAmerican Decorative Arts
5th rowAmerican Decorative Arts

Common Values

ValueCountFrequency (%)
Drawings and Prints154445
34.5%
European Sculpture and Decorative Arts42528
 
9.5%
Asian Art36727
 
8.2%
Photographs36258
 
8.1%
Costume Institute33681
 
7.5%
Egyptian Art27542
 
6.1%
Greek and Roman Art17292
 
3.9%
Islamic Art15082
 
3.4%
Modern and Contemporary Art13991
 
3.1%
Arms and Armor13486
 
3.0%
Other values (10)57171
 
12.8%

Length

2025-10-24T01:14:28.602663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
and259620
19.7%
drawings154445
11.7%
prints154445
11.7%
art124162
 
9.4%
arts67285
 
5.1%
decorative54858
 
4.2%
sculpture47979
 
3.6%
european45288
 
3.4%
asian36727
 
2.8%
photographs36258
 
2.7%
Other values (28)337488
25.6%

Most occurring characters

ValueCountFrequency (%)
870352
 
10.0%
r850278
 
9.8%
n837991
 
9.6%
a764563
 
8.8%
t712664
 
8.2%
s593233
 
6.8%
i572622
 
6.6%
e439850
 
5.1%
A303966
 
3.5%
o301916
 
3.5%
Other values (28)2461724
28.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)8709159
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
870352
 
10.0%
r850278
 
9.8%
n837991
 
9.6%
a764563
 
8.8%
t712664
 
8.2%
s593233
 
6.8%
i572622
 
6.6%
e439850
 
5.1%
A303966
 
3.5%
o301916
 
3.5%
Other values (28)2461724
28.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)8709159
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
870352
 
10.0%
r850278
 
9.8%
n837991
 
9.6%
a764563
 
8.8%
t712664
 
8.2%
s593233
 
6.8%
i572622
 
6.6%
e439850
 
5.1%
A303966
 
3.5%
o301916
 
3.5%
Other values (28)2461724
28.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)8709159
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
870352
 
10.0%
r850278
 
9.8%
n837991
 
9.6%
a764563
 
8.8%
t712664
 
8.2%
s593233
 
6.8%
i572622
 
6.6%
e439850
 
5.1%
A303966
 
3.5%
o301916
 
3.5%
Other values (28)2461724
28.3%
Distinct27037
Distinct (%)6.1%
Missing2635
Missing (%)0.6%
Memory size3.4 MiB
2025-10-24T01:14:28.743675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length80
Median length77
Mean length10.207537
Min length2

Characters and Unicode

Total characters4548152
Distinct characters133
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17615 ?
Unique (%)4.0%

Sample

1st rowCoin
2nd rowCoin
3rd rowCoin
4th rowCoin
5th rowCoin
ValueCountFrequency (%)
print104426
 
14.9%
photograph31124
 
4.4%
drawing28773
 
4.1%
book18301
 
2.6%
ornament17234
 
2.5%
fragment15927
 
2.3%
15275
 
2.2%
architecture14725
 
2.1%
card13246
 
1.9%
baseball12813
 
1.8%
Other values (10416)430871
61.3%
2025-10-24T01:14:29.028937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r396208
 
8.7%
e367342
 
8.1%
t366197
 
8.1%
a358210
 
7.9%
n332429
 
7.3%
i315620
 
6.9%
257078
 
5.7%
o255834
 
5.6%
P170519
 
3.7%
l170490
 
3.7%
Other values (123)1558225
34.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)4548152
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r396208
 
8.7%
e367342
 
8.1%
t366197
 
8.1%
a358210
 
7.9%
n332429
 
7.3%
i315620
 
6.9%
257078
 
5.7%
o255834
 
5.6%
P170519
 
3.7%
l170490
 
3.7%
Other values (123)1558225
34.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4548152
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r396208
 
8.7%
e367342
 
8.1%
t366197
 
8.1%
a358210
 
7.9%
n332429
 
7.3%
i315620
 
6.9%
257078
 
5.7%
o255834
 
5.6%
P170519
 
3.7%
l170490
 
3.7%
Other values (123)1558225
34.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4548152
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r396208
 
8.7%
e367342
 
8.1%
t366197
 
8.1%
a358210
 
7.9%
n332429
 
7.3%
i315620
 
6.9%
257078
 
5.7%
o255834
 
5.6%
P170519
 
3.7%
l170490
 
3.7%
Other values (123)1558225
34.3%

Title
Text

Missing 

Distinct225553
Distinct (%)54.1%
Missing31447
Missing (%)7.0%
Memory size3.4 MiB
2025-10-24T01:14:29.304164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length831
Median length696
Mean length39.87253
Min length1

Characters and Unicode

Total characters16617116
Distinct characters3282
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique197470 ?
Unique (%)47.4%

Sample

1st rowOne-dollar Liberty Head Coin
2nd rowTen-dollar Liberty Head Coin
3rd rowTwo-and-a-Half Dollar Coin
4th rowTwo-and-a-Half Dollar Coin
5th rowTwo-and-a-Half Dollar Coin
ValueCountFrequency (%)
the126377
 
4.7%
of97856
 
3.7%
from73269
 
2.7%
a54584
 
2.0%
and49220
 
1.8%
series40158
 
1.5%
with31811
 
1.2%
for30777
 
1.2%
by28964
 
1.1%
in28714
 
1.1%
Other values (112220)2105867
78.9%
2025-10-24T01:14:29.715714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2258127
 
13.6%
e1554841
 
9.4%
a1057811
 
6.4%
r971399
 
5.8%
o938988
 
5.7%
i894830
 
5.4%
t867645
 
5.2%
n811784
 
4.9%
s791203
 
4.8%
l539534
 
3.2%
Other values (3272)5930954
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)16617116
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2258127
 
13.6%
e1554841
 
9.4%
a1057811
 
6.4%
r971399
 
5.8%
o938988
 
5.7%
i894830
 
5.4%
t867645
 
5.2%
n811784
 
4.9%
s791203
 
4.8%
l539534
 
3.2%
Other values (3272)5930954
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)16617116
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2258127
 
13.6%
e1554841
 
9.4%
a1057811
 
6.4%
r971399
 
5.8%
o938988
 
5.7%
i894830
 
5.4%
t867645
 
5.2%
n811784
 
4.9%
s791203
 
4.8%
l539534
 
3.2%
Other values (3272)5930954
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)16617116
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2258127
 
13.6%
e1554841
 
9.4%
a1057811
 
6.4%
r971399
 
5.8%
o938988
 
5.7%
i894830
 
5.4%
t867645
 
5.2%
n811784
 
4.9%
s791203
 
4.8%
l539534
 
3.2%
Other values (3272)5930954
35.7%

Culture
Text

Missing 

Distinct7101
Distinct (%)3.8%
Missing261685
Missing (%)58.4%
Memory size3.4 MiB
2025-10-24T01:14:29.874562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length64
Median length62
Mean length9.8933883
Min length2

Characters and Unicode

Total characters1845295
Distinct characters111
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4020 ?
Unique (%)2.2%

Sample

1st rowAmerican
2nd rowAmerican
3rd rowAmerican
4th rowAmerican
5th rowBritish (American market)
ValueCountFrequency (%)
american26650
 
10.0%
french24957
 
9.3%
japan16512
 
6.2%
china14383
 
5.4%
italian12669
 
4.7%
british11431
 
4.3%
german8997
 
3.4%
or7600
 
2.8%
european6513
 
2.4%
japanese6191
 
2.3%
Other values (3786)131551
49.2%
2025-10-24T01:14:30.107824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a222180
 
12.0%
n192232
 
10.4%
e154709
 
8.4%
i143946
 
7.8%
r139829
 
7.6%
81003
 
4.4%
h77570
 
4.2%
c71629
 
3.9%
o68489
 
3.7%
s68248
 
3.7%
Other values (101)625460
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)1845295
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a222180
 
12.0%
n192232
 
10.4%
e154709
 
8.4%
i143946
 
7.8%
r139829
 
7.6%
81003
 
4.4%
h77570
 
4.2%
c71629
 
3.9%
o68489
 
3.7%
s68248
 
3.7%
Other values (101)625460
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1845295
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a222180
 
12.0%
n192232
 
10.4%
e154709
 
8.4%
i143946
 
7.8%
r139829
 
7.6%
81003
 
4.4%
h77570
 
4.2%
c71629
 
3.9%
o68489
 
3.7%
s68248
 
3.7%
Other values (101)625460
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1845295
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a222180
 
12.0%
n192232
 
10.4%
e154709
 
8.4%
i143946
 
7.8%
r139829
 
7.6%
81003
 
4.4%
h77570
 
4.2%
c71629
 
3.9%
o68489
 
3.7%
s68248
 
3.7%
Other values (101)625460
33.9%

Period
Unsupported

Missing  Rejected  Unsupported 

Missing376321
Missing (%)84.0%
Memory size3.4 MiB

Dynasty
Text

Missing 

Distinct341
Distinct (%)1.5%
Missing425185
Missing (%)94.9%
Memory size3.4 MiB
2025-10-24T01:14:30.239678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length45
Median length10
Mean length11.718698
Min length1

Characters and Unicode

Total characters269741
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)0.7%

Sample

1st rowDynasty 8–11
2nd rowDynasty 12
3rd rowearly Dynasty 18
4th rowDynasty 1
5th rowDynasty 12
ValueCountFrequency (%)
dynasty23130
47.4%
187631
 
15.6%
122601
 
5.3%
19–201990
 
4.1%
12–131257
 
2.6%
191172
 
2.4%
21940
 
1.9%
early813
 
1.7%
26–30783
 
1.6%
26665
 
1.4%
Other values (209)7815
 
16.0%
2025-10-24T01:14:30.456282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y47453
17.6%
25782
9.6%
a25018
9.3%
124002
8.9%
t23875
8.9%
n23312
8.6%
s23237
8.6%
D23146
8.6%
212171
 
4.5%
88794
 
3.3%
Other values (46)32951
12.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)269741
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
y47453
17.6%
25782
9.6%
a25018
9.3%
124002
8.9%
t23875
8.9%
n23312
8.6%
s23237
8.6%
D23146
8.6%
212171
 
4.5%
88794
 
3.3%
Other values (46)32951
12.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)269741
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
y47453
17.6%
25782
9.6%
a25018
9.3%
124002
8.9%
t23875
8.9%
n23312
8.6%
s23237
8.6%
D23146
8.6%
212171
 
4.5%
88794
 
3.3%
Other values (46)32951
12.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)269741
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
y47453
17.6%
25782
9.6%
a25018
9.3%
124002
8.9%
t23875
8.9%
n23312
8.6%
s23237
8.6%
D23146
8.6%
212171
 
4.5%
88794
 
3.3%
Other values (46)32951
12.2%

Reign
Text

Missing 

Distinct356
Distinct (%)3.3%
Missing437386
Missing (%)97.6%
Memory size3.4 MiB
2025-10-24T01:14:30.556508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length55
Median length50
Mean length23.88287
Min length3

Characters and Unicode

Total characters258341
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique179 ?
Unique (%)1.7%

Sample

1st rowreign of Amenemhat II
2nd rowreign of Ahmose I to Hatshepsut
3rd rowreign of Amenemhat IV
4th rowreign of Thutmose II–Early Joint reign
5th rowreign of Pepi II
ValueCountFrequency (%)
reign10784
23.0%
of10650
22.7%
iii4257
 
9.1%
amenhotep2662
 
5.7%
i2603
 
5.6%
thutmose2027
 
4.3%
early1404
 
3.0%
amenemhat1397
 
3.0%
ii1202
 
2.6%
joint1151
 
2.5%
Other values (203)8733
18.6%
2025-10-24T01:14:30.793754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36056
14.0%
e31375
12.1%
n21101
 
8.2%
I19306
 
7.5%
o18081
 
7.0%
i13548
 
5.2%
r13446
 
5.2%
t12945
 
5.0%
g10836
 
4.2%
f10705
 
4.1%
Other values (54)70942
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)258341
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
36056
14.0%
e31375
12.1%
n21101
 
8.2%
I19306
 
7.5%
o18081
 
7.0%
i13548
 
5.2%
r13446
 
5.2%
t12945
 
5.0%
g10836
 
4.2%
f10705
 
4.1%
Other values (54)70942
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)258341
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
36056
14.0%
e31375
12.1%
n21101
 
8.2%
I19306
 
7.5%
o18081
 
7.0%
i13548
 
5.2%
r13446
 
5.2%
t12945
 
5.0%
g10836
 
4.2%
f10705
 
4.1%
Other values (54)70942
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)258341
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
36056
14.0%
e31375
12.1%
n21101
 
8.2%
I19306
 
7.5%
o18081
 
7.0%
i13548
 
5.2%
r13446
 
5.2%
t12945
 
5.0%
g10836
 
4.2%
f10705
 
4.1%
Other values (54)70942
27.5%

Portfolio
Text

Missing 

Distinct2908
Distinct (%)14.3%
Missing427833
Missing (%)95.5%
Memory size3.4 MiB
2025-10-24T01:14:31.024635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length835
Median length298
Mean length59.781885
Min length1

Characters and Unicode

Total characters1217757
Distinct characters110
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1425 ?
Unique (%)7.0%

Sample

1st rowLa Tauromaquia
2nd rowLa Tauromaquia
3rd rowLa Tauromaquia
4th rowLos Caprichos
5th rowLos Caprichos
ValueCountFrequency (%)
de10588
 
5.7%
les6159
 
3.3%
of5076
 
2.7%
the5013
 
2.7%
et4287
 
2.3%
la3377
 
1.8%
di1813
 
1.0%
le1812
 
1.0%
and1638
 
0.9%
par1408
 
0.8%
Other values (4721)145466
77.9%
2025-10-24T01:14:31.337926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166262
13.7%
e136493
 
11.2%
i81842
 
6.7%
a76442
 
6.3%
s73665
 
6.0%
r64837
 
5.3%
t58542
 
4.8%
o57379
 
4.7%
n55300
 
4.5%
l38515
 
3.2%
Other values (100)408480
33.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)1217757
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
166262
13.7%
e136493
 
11.2%
i81842
 
6.7%
a76442
 
6.3%
s73665
 
6.0%
r64837
 
5.3%
t58542
 
4.8%
o57379
 
4.7%
n55300
 
4.5%
l38515
 
3.2%
Other values (100)408480
33.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1217757
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
166262
13.7%
e136493
 
11.2%
i81842
 
6.7%
a76442
 
6.3%
s73665
 
6.0%
r64837
 
5.3%
t58542
 
4.8%
o57379
 
4.7%
n55300
 
4.5%
l38515
 
3.2%
Other values (100)408480
33.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1217757
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
166262
13.7%
e136493
 
11.2%
i81842
 
6.7%
a76442
 
6.3%
s73665
 
6.0%
r64837
 
5.3%
t58542
 
4.8%
o57379
 
4.7%
n55300
 
4.5%
l38515
 
3.2%
Other values (100)408480
33.5%

Artist Role
Text

Missing 

Distinct5664
Distinct (%)2.2%
Missing188294
Missing (%)42.0%
Memory size3.4 MiB
2025-10-24T01:14:31.449086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1276
Median length957
Mean length11.776456
Min length1

Characters and Unicode

Total characters3060807
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3902 ?
Unique (%)1.5%

Sample

1st rowMaker
2nd rowMaker
3rd rowMaker
4th rowMaker
5th rowMaker
ValueCountFrequency (%)
artist108804
39.7%
publisher36389
 
13.3%
artist|artist10817
 
3.9%
designer10585
 
3.9%
artist|publisher10559
 
3.9%
maker9813
 
3.6%
house3626
 
1.3%
manufacturer3535
 
1.3%
author3376
 
1.2%
publisher|lithographer2985
 
1.1%
Other values (5455)73364
26.8%
2025-10-24T01:14:31.664794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t465039
15.2%
r434821
14.2%
i336566
11.0%
s315718
10.3%
e212111
 
6.9%
A207531
 
6.8%
|134969
 
4.4%
u129424
 
4.2%
h119545
 
3.9%
P100506
 
3.3%
Other values (34)604577
19.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)3060807
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t465039
15.2%
r434821
14.2%
i336566
11.0%
s315718
10.3%
e212111
 
6.9%
A207531
 
6.8%
|134969
 
4.4%
u129424
 
4.2%
h119545
 
3.9%
P100506
 
3.3%
Other values (34)604577
19.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3060807
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t465039
15.2%
r434821
14.2%
i336566
11.0%
s315718
10.3%
e212111
 
6.9%
A207531
 
6.8%
|134969
 
4.4%
u129424
 
4.2%
h119545
 
3.9%
P100506
 
3.3%
Other values (34)604577
19.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3060807
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t465039
15.2%
r434821
14.2%
i336566
11.0%
s315718
10.3%
e212111
 
6.9%
A207531
 
6.8%
|134969
 
4.4%
u129424
 
4.2%
h119545
 
3.9%
P100506
 
3.3%
Other values (34)604577
19.8%

Artist Prefix
Text

Missing 

Distinct5290
Distinct (%)5.9%
Missing359275
Missing (%)80.2%
Memory size3.4 MiB
2025-10-24T01:14:31.810780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1239
Median length1195
Mean length14.697755
Min length1

Characters and Unicode

Total characters1307042
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3788 ?
Unique (%)4.3%

Sample

1st rowDesigned by|Manufactured by
2nd rowAttributed to
3rd rowAttributed to
4th rowDesigned by
5th rowDesigned by
ValueCountFrequency (%)
by55716
26.7%
issued33186
15.9%
after17181
 
8.2%
published7098
 
3.4%
to6952
 
3.3%
attributed6933
 
3.3%
of5175
 
2.5%
the4978
 
2.4%
by|published4200
 
2.0%
written3323
 
1.6%
Other values (2839)64132
30.7%
2025-10-24T01:14:32.042561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e129758
 
9.9%
120036
 
9.2%
s105627
 
8.1%
b100640
 
7.7%
t95585
 
7.3%
d84515
 
6.5%
y83385
 
6.4%
r68786
 
5.3%
u60751
 
4.6%
i55837
 
4.3%
Other values (76)402122
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)1307042
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e129758
 
9.9%
120036
 
9.2%
s105627
 
8.1%
b100640
 
7.7%
t95585
 
7.3%
d84515
 
6.5%
y83385
 
6.4%
r68786
 
5.3%
u60751
 
4.6%
i55837
 
4.3%
Other values (76)402122
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1307042
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e129758
 
9.9%
120036
 
9.2%
s105627
 
8.1%
b100640
 
7.7%
t95585
 
7.3%
d84515
 
6.5%
y83385
 
6.4%
r68786
 
5.3%
u60751
 
4.6%
i55837
 
4.3%
Other values (76)402122
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1307042
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e129758
 
9.9%
120036
 
9.2%
s105627
 
8.1%
b100640
 
7.7%
t95585
 
7.3%
d84515
 
6.5%
y83385
 
6.4%
r68786
 
5.3%
u60751
 
4.6%
i55837
 
4.3%
Other values (76)402122
30.8%

Artist Display Name
Text

Missing 

Distinct56390
Distinct (%)21.6%
Missing187092
Missing (%)41.7%
Memory size3.4 MiB
2025-10-24T01:14:32.249441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3620
Median length996
Mean length27.786079
Min length1

Characters and Unicode

Total characters7255251
Distinct characters163
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39185 ?
Unique (%)15.0%

Sample

1st rowJames Barton Longacre
2nd rowChristian Gobrecht
3rd rowBela Lyon Pratt
4th rowChristian Gobrecht
5th rowJames Barton Longacre
ValueCountFrequency (%)
33432
 
3.6%
company20979
 
2.2%
de13013
 
1.4%
co11786
 
1.3%
walker9904
 
1.1%
evans9897
 
1.1%
sons7406
 
0.8%
gum7128
 
0.8%
anonymous6892
 
0.7%
and6718
 
0.7%
Other values (79028)812845
86.5%
2025-10-24T01:14:32.561006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
679513
 
9.4%
e620956
 
8.6%
a560600
 
7.7%
n496755
 
6.8%
r447330
 
6.2%
o446355
 
6.2%
i414937
 
5.7%
l305995
 
4.2%
s284518
 
3.9%
t268257
 
3.7%
Other values (153)2730035
37.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)7255251
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
679513
 
9.4%
e620956
 
8.6%
a560600
 
7.7%
n496755
 
6.8%
r447330
 
6.2%
o446355
 
6.2%
i414937
 
5.7%
l305995
 
4.2%
s284518
 
3.9%
t268257
 
3.7%
Other values (153)2730035
37.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)7255251
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
679513
 
9.4%
e620956
 
8.6%
a560600
 
7.7%
n496755
 
6.8%
r447330
 
6.2%
o446355
 
6.2%
i414937
 
5.7%
l305995
 
4.2%
s284518
 
3.9%
t268257
 
3.7%
Other values (153)2730035
37.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)7255251
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
679513
 
9.4%
e620956
 
8.6%
a560600
 
7.7%
n496755
 
6.8%
r447330
 
6.2%
o446355
 
6.2%
i414937
 
5.7%
l305995
 
4.2%
s284518
 
3.9%
t268257
 
3.7%
Other values (153)2730035
37.6%

Artist Display Bio
Text

Missing 

Distinct40951
Distinct (%)18.3%
Missing224139
Missing (%)50.0%
Memory size3.4 MiB
2025-10-24T01:14:32.738537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6227
Median length1461
Mean length45.138652
Min length1

Characters and Unicode

Total characters10113947
Distinct characters125
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26627 ?
Unique (%)11.9%

Sample

1st rowAmerican, Delaware County, Pennsylvania 1794–1869 Philadelphia, Pennsylvania
2nd row1785–1844
3rd row1867–1917
4th row1785–1844
5th rowAmerican, Delaware County, Pennsylvania 1794–1869 Philadelphia, Pennsylvania
ValueCountFrequency (%)
american75807
 
6.5%
new49412
 
4.2%
french40660
 
3.5%
paris35776
 
3.1%
york32674
 
2.8%
born28348
 
2.4%
active25244
 
2.2%
italian21392
 
1.8%
ca20444
 
1.7%
british19060
 
1.6%
Other values (34149)823725
70.3%
2025-10-24T01:14:32.955095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
949444
 
9.4%
e621003
 
6.1%
n611922
 
6.1%
1588624
 
5.8%
a578157
 
5.7%
r549438
 
5.4%
i510974
 
5.1%
,387024
 
3.8%
o343193
 
3.4%
c325945
 
3.2%
Other values (115)4648223
46.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)10113947
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
949444
 
9.4%
e621003
 
6.1%
n611922
 
6.1%
1588624
 
5.8%
a578157
 
5.7%
r549438
 
5.4%
i510974
 
5.1%
,387024
 
3.8%
o343193
 
3.4%
c325945
 
3.2%
Other values (115)4648223
46.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)10113947
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
949444
 
9.4%
e621003
 
6.1%
n611922
 
6.1%
1588624
 
5.8%
a578157
 
5.7%
r549438
 
5.4%
i510974
 
5.1%
,387024
 
3.8%
o343193
 
3.4%
c325945
 
3.2%
Other values (115)4648223
46.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)10113947
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
949444
 
9.4%
e621003
 
6.1%
n611922
 
6.1%
1588624
 
5.8%
a578157
 
5.7%
r549438
 
5.4%
i510974
 
5.1%
,387024
 
3.8%
o343193
 
3.4%
c325945
 
3.2%
Other values (115)4648223
46.0%

Artist Suffix
Text

Missing 

Distinct1644
Distinct (%)16.1%
Missing437991
Missing (%)97.7%
Memory size3.4 MiB
2025-10-24T01:14:33.091796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1281
Median length486
Mean length12.40237
Min length1

Characters and Unicode

Total characters126653
Distinct characters91
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1255 ?
Unique (%)12.3%

Sample

1st rowor
2nd rowor
3rd rowor
4th rowor
5th rowor
ValueCountFrequency (%)
8144
31.0%
paris2998
 
11.4%
venice1012
 
3.9%
and622
 
2.4%
the453
 
1.7%
london391
 
1.5%
of366
 
1.4%
or353
 
1.3%
new323
 
1.2%
york313
 
1.2%
Other values (2094)11291
43.0%
2025-10-24T01:14:33.362480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16078
 
12.7%
a9413
 
7.4%
e8904
 
7.0%
,8796
 
6.9%
r8416
 
6.6%
i7742
 
6.1%
n7555
 
6.0%
o5875
 
4.6%
s5776
 
4.6%
t3696
 
2.9%
Other values (81)44402
35.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)126653
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
16078
 
12.7%
a9413
 
7.4%
e8904
 
7.0%
,8796
 
6.9%
r8416
 
6.6%
i7742
 
6.1%
n7555
 
6.0%
o5875
 
4.6%
s5776
 
4.6%
t3696
 
2.9%
Other values (81)44402
35.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)126653
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
16078
 
12.7%
a9413
 
7.4%
e8904
 
7.0%
,8796
 
6.9%
r8416
 
6.6%
i7742
 
6.1%
n7555
 
6.0%
o5875
 
4.6%
s5776
 
4.6%
t3696
 
2.9%
Other values (81)44402
35.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)126653
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
16078
 
12.7%
a9413
 
7.4%
e8904
 
7.0%
,8796
 
6.9%
r8416
 
6.6%
i7742
 
6.1%
n7555
 
6.0%
o5875
 
4.6%
s5776
 
4.6%
t3696
 
2.9%
Other values (81)44402
35.1%

Artist Alpha Sort
Text

Missing 

Distinct56400
Distinct (%)21.6%
Missing187115
Missing (%)41.7%
Memory size3.4 MiB
2025-10-24T01:14:33.580603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3724
Median length1032
Mean length28.059991
Min length1

Characters and Unicode

Total characters7326127
Distinct characters154
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39188 ?
Unique (%)15.0%

Sample

1st rowLongacre, James Barton
2nd rowGobrecht, Christian
3rd rowPratt, Bela Lyon
4th rowGobrecht, Christian
5th rowLongacre, James Barton
ValueCountFrequency (%)
33178
 
3.6%
company20766
 
2.3%
co11640
 
1.3%
evans9957
 
1.1%
walker9768
 
1.1%
de9481
 
1.0%
sons7449
 
0.8%
john7307
 
0.8%
gum7101
 
0.8%
w7046
 
0.8%
Other values (80307)793296
86.5%
2025-10-24T01:14:33.925060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
658400
 
9.0%
e604049
 
8.2%
a544239
 
7.4%
n485136
 
6.6%
r436085
 
6.0%
o434723
 
5.9%
i401518
 
5.5%
l297146
 
4.1%
,291351
 
4.0%
s274419
 
3.7%
Other values (144)2899061
39.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)7326127
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
658400
 
9.0%
e604049
 
8.2%
a544239
 
7.4%
n485136
 
6.6%
r436085
 
6.0%
o434723
 
5.9%
i401518
 
5.5%
l297146
 
4.1%
,291351
 
4.0%
s274419
 
3.7%
Other values (144)2899061
39.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)7326127
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
658400
 
9.0%
e604049
 
8.2%
a544239
 
7.4%
n485136
 
6.6%
r436085
 
6.0%
o434723
 
5.9%
i401518
 
5.5%
l297146
 
4.1%
,291351
 
4.0%
s274419
 
3.7%
Other values (144)2899061
39.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)7326127
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
658400
 
9.0%
e604049
 
8.2%
a544239
 
7.4%
n485136
 
6.6%
r436085
 
6.0%
o434723
 
5.9%
i401518
 
5.5%
l297146
 
4.1%
,291351
 
4.0%
s274419
 
3.7%
Other values (144)2899061
39.6%

Artist Nationality
Text

Missing 

Distinct3811
Distinct (%)1.9%
Missing252071
Missing (%)56.2%
Memory size3.4 MiB
2025-10-24T01:14:34.064843image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1494
Median length1109
Mean length12.14553
Min length4

Characters and Unicode

Total characters2382127
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2417 ?
Unique (%)1.2%

Sample

1st rowAmerican
2nd rowAmerican
3rd rowAmerican
4th rowFrench
5th rowFrench
ValueCountFrequency (%)
american69139
31.8%
french19746
 
9.1%
italian12818
 
5.9%
british10727
 
4.9%
french|french9259
 
4.3%
born8250
 
3.8%
american|american7819
 
3.6%
german7584
 
3.5%
japanese6284
 
2.9%
italian|italian4535
 
2.1%
Other values (3278)61443
28.2%
2025-10-24T01:14:34.315917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n266797
11.2%
r243241
10.2%
i236835
9.9%
e232941
9.8%
a230819
9.7%
c175755
 
7.4%
h146011
 
6.1%
m117011
 
4.9%
A98145
 
4.1%
t97443
 
4.1%
Other values (62)537129
22.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)2382127
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n266797
11.2%
r243241
10.2%
i236835
9.9%
e232941
9.8%
a230819
9.7%
c175755
 
7.4%
h146011
 
6.1%
m117011
 
4.9%
A98145
 
4.1%
t97443
 
4.1%
Other values (62)537129
22.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2382127
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n266797
11.2%
r243241
10.2%
i236835
9.9%
e232941
9.8%
a230819
9.7%
c175755
 
7.4%
h146011
 
6.1%
m117011
 
4.9%
A98145
 
4.1%
t97443
 
4.1%
Other values (62)537129
22.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2382127
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n266797
11.2%
r243241
10.2%
i236835
9.9%
e232941
9.8%
a230819
9.7%
c175755
 
7.4%
h146011
 
6.1%
m117011
 
4.9%
A98145
 
4.1%
t97443
 
4.1%
Other values (62)537129
22.5%

Artist Begin Date
Text

Missing 

Distinct20795
Distinct (%)9.7%
Missing232969
Missing (%)52.0%
Memory size3.4 MiB
2025-10-24T01:14:34.543328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1990
Median length10
Mean length14.97099
Min length10

Characters and Unicode

Total characters3222266
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14453 ?
Unique (%)6.7%

Sample

1st row1794
2nd row1785
3rd row1867
4th row1785
5th row1794
ValueCountFrequency (%)
180012295
 
3.9%
190311150
 
3.6%
18508249
 
2.6%
18706867
 
2.2%
19005635
 
1.8%
17004140
 
1.3%
15003015
 
1.0%
18292810
 
0.9%
15922438
 
0.8%
15102358
 
0.8%
Other values (1123)252620
81.1%
2025-10-24T01:14:34.855334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1861826
57.8%
1363551
 
11.3%
8163372
 
5.1%
0153958
 
4.8%
7114134
 
3.5%
9106983
 
3.3%
5102027
 
3.2%
|97266
 
3.0%
674749
 
2.3%
361626
 
1.9%
Other values (3)122774
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)3222266
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1861826
57.8%
1363551
 
11.3%
8163372
 
5.1%
0153958
 
4.8%
7114134
 
3.5%
9106983
 
3.3%
5102027
 
3.2%
|97266
 
3.0%
674749
 
2.3%
361626
 
1.9%
Other values (3)122774
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3222266
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1861826
57.8%
1363551
 
11.3%
8163372
 
5.1%
0153958
 
4.8%
7114134
 
3.5%
9106983
 
3.3%
5102027
 
3.2%
|97266
 
3.0%
674749
 
2.3%
361626
 
1.9%
Other values (3)122774
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3222266
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1861826
57.8%
1363551
 
11.3%
8163372
 
5.1%
0153958
 
4.8%
7114134
 
3.5%
9106983
 
3.3%
5102027
 
3.2%
|97266
 
3.0%
674749
 
2.3%
361626
 
1.9%
Other values (3)122774
 
3.8%

Artist End Date
Text

Missing 

Distinct21229
Distinct (%)10.0%
Missing235378
Missing (%)52.5%
Memory size3.4 MiB
2025-10-24T01:14:35.068283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1990
Median length10
Mean length15.022709
Min length10

Characters and Unicode

Total characters3197208
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14879 ?
Unique (%)7.0%

Sample

1st row1869
2nd row1844
3rd row1917
4th row1844
5th row1869
ValueCountFrequency (%)
190010889
 
3.5%
197510404
 
3.4%
99997967
 
2.6%
19507536
 
2.4%
19206912
 
2.2%
19994712
 
1.5%
18003779
 
1.2%
16352598
 
0.8%
18502333
 
0.8%
18992251
 
0.7%
Other values (1133)249983
80.8%
2025-10-24T01:14:35.295578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1850488
57.9%
1326869
 
10.2%
9204181
 
6.4%
0135854
 
4.2%
8124504
 
3.9%
|97178
 
3.0%
595715
 
3.0%
794934
 
3.0%
693280
 
2.9%
276533
 
2.4%
Other values (3)97672
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)3197208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1850488
57.9%
1326869
 
10.2%
9204181
 
6.4%
0135854
 
4.2%
8124504
 
3.9%
|97178
 
3.0%
595715
 
3.0%
794934
 
3.0%
693280
 
2.9%
276533
 
2.4%
Other values (3)97672
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3197208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1850488
57.9%
1326869
 
10.2%
9204181
 
6.4%
0135854
 
4.2%
8124504
 
3.9%
|97178
 
3.0%
595715
 
3.0%
794934
 
3.0%
693280
 
2.9%
276533
 
2.4%
Other values (3)97672
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3197208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1850488
57.9%
1326869
 
10.2%
9204181
 
6.4%
0135854
 
4.2%
8124504
 
3.9%
|97178
 
3.0%
595715
 
3.0%
794934
 
3.0%
693280
 
2.9%
276533
 
2.4%
Other values (3)97672
 
3.1%

Object Date
Text

Missing 

Distinct29630
Distinct (%)6.8%
Missing15594
Missing (%)3.5%
Memory size3.4 MiB
2025-10-24T01:14:35.423954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length239
Median length139
Mean length10.918522
Min length1

Characters and Unicode

Total characters4723451
Distinct characters99
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17250 ?
Unique (%)4.0%

Sample

1st row1853
2nd row1901
3rd row1909–27
4th row1909–27
5th row1909–27
ValueCountFrequency (%)
century123272
 
14.9%
ca100040
 
12.1%
b.c41717
 
5.1%
19th26470
 
3.2%
late15622
 
1.9%
18th15477
 
1.9%
20th10149
 
1.2%
17th9582
 
1.2%
early9526
 
1.2%
18887192
 
0.9%
Other values (13362)465827
56.5%
2025-10-24T01:14:35.619479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1525581
 
11.1%
394079
 
8.3%
t319368
 
6.8%
9233257
 
4.9%
c232051
 
4.9%
0225802
 
4.8%
.216592
 
4.6%
8215705
 
4.6%
e195899
 
4.1%
r181824
 
3.8%
Other values (89)1983293
42.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)4723451
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1525581
 
11.1%
394079
 
8.3%
t319368
 
6.8%
9233257
 
4.9%
c232051
 
4.9%
0225802
 
4.8%
.216592
 
4.6%
8215705
 
4.6%
e195899
 
4.1%
r181824
 
3.8%
Other values (89)1983293
42.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4723451
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1525581
 
11.1%
394079
 
8.3%
t319368
 
6.8%
9233257
 
4.9%
c232051
 
4.9%
0225802
 
4.8%
.216592
 
4.6%
8215705
 
4.6%
e195899
 
4.1%
r181824
 
3.8%
Other values (89)1983293
42.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4723451
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1525581
 
11.1%
394079
 
8.3%
t319368
 
6.8%
9233257
 
4.9%
c232051
 
4.9%
0225802
 
4.8%
.216592
 
4.6%
8215705
 
4.6%
e195899
 
4.1%
r181824
 
3.8%
Other values (89)1983293
42.0%

Object Begin Date
Real number (ℝ)

High correlation  Skewed 

Distinct2074
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1390.8172
Minimum-95000
Maximum18591861
Zeros1251
Zeros (%)0.3%
Negative50473
Negative (%)11.3%
Memory size3.4 MiB
2025-10-24T01:14:35.663098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-95000
5-th percentile-1390
Q11567
median1800
Q31895
95-th percentile1965
Maximum18591861
Range18686861
Interquartile range (IQR)328

Descriptive statistics

Standard deviation27798.159
Coefficient of variation (CV)19.986925
Kurtosis446299.56
Mean1390.8172
Median Absolute Deviation (MAD)122
Skewness667.34463
Sum6.2336843 × 108
Variance7.7273765 × 108
MonotonicityNot monotonic
2025-10-24T01:14:35.709975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
180023579
 
5.3%
170016355
 
3.6%
190010583
 
2.4%
16007157
 
1.6%
18885936
 
1.3%
18505834
 
1.3%
18905771
 
1.3%
15005604
 
1.3%
18804690
 
1.0%
19104528
 
1.0%
Other values (2064)358166
79.9%
ValueCountFrequency (%)
-950001
 
< 0.1%
-9000015
 
< 0.1%
-125002
 
< 0.1%
-110005
 
< 0.1%
-1002511
 
< 0.1%
-100005
 
< 0.1%
-80008
 
< 0.1%
-750020
 
< 0.1%
-725023
 
< 0.1%
-70001718
0.4%
ValueCountFrequency (%)
185918611
 
< 0.1%
50002
 
< 0.1%
201644
 
< 0.1%
201596
< 0.1%
201475
< 0.1%
201382
< 0.1%
2012151
< 0.1%
2011124
< 0.1%
201095
< 0.1%
2009146
< 0.1%

Object End Date
Real number (ℝ)

High correlation  Skewed 

Distinct2033
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1493.4464
Minimum-35000
Maximum18591861
Zeros1230
Zeros (%)0.3%
Negative43494
Negative (%)9.7%
Memory size3.4 MiB
2025-10-24T01:14:35.758764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-35000
5-th percentile-1279
Q11600
median1850
Q31910
95-th percentile1974
Maximum18591861
Range18626861
Interquartile range (IQR)310

Descriptive statistics

Standard deviation27787.124
Coefficient of variation (CV)18.606041
Kurtosis446999.07
Mean1493.4464
Median Absolute Deviation (MAD)90
Skewness668.13111
Sum6.6936714 × 108
Variance7.7212426 × 108
MonotonicityNot monotonic
2025-10-24T01:14:35.976417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
189920830
 
4.6%
190012736
 
2.8%
179911460
 
2.6%
18906482
 
1.4%
18896391
 
1.4%
16995215
 
1.2%
18884964
 
1.1%
18004353
 
1.0%
20004232
 
0.9%
19104106
 
0.9%
Other values (2023)367434
82.0%
ValueCountFrequency (%)
-350001
 
< 0.1%
-93004
 
< 0.1%
-700031
 
< 0.1%
-68841
 
< 0.1%
-64002
 
< 0.1%
-60004
 
< 0.1%
-58007
 
< 0.1%
-55001
 
< 0.1%
-54005
 
< 0.1%
-500083
< 0.1%
ValueCountFrequency (%)
185918611
< 0.1%
1575551
< 0.1%
1535051
< 0.1%
153351
< 0.1%
99001
< 0.1%
28701
< 0.1%
28351
< 0.1%
20992
< 0.1%
20891
< 0.1%
20781
< 0.1%

Medium
Text

Missing 

Distinct61445
Distinct (%)14.0%
Missing8048
Missing (%)1.8%
Memory size3.4 MiB
2025-10-24T01:14:36.161465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length8249
Median length464
Mean length21.948927
Min length1

Characters and Unicode

Total characters9660930
Distinct characters121
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47671 ?
Unique (%)10.8%

Sample

1st rowGold
2nd rowGold
3rd rowGold
4th rowGold
5th rowGold
ValueCountFrequency (%)
and73075
 
5.1%
on43270
 
3.0%
lithograph37288
 
2.6%
color36224
 
2.5%
silk35813
 
2.5%
etching35799
 
2.5%
ink33991
 
2.4%
paper32999
 
2.3%
silver32889
 
2.3%
print30467
 
2.1%
Other values (10179)1033484
72.5%
2025-10-24T01:14:36.431952image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
987386
 
10.2%
e754882
 
7.8%
o716244
 
7.4%
a705127
 
7.3%
r637989
 
6.6%
n629844
 
6.5%
i600667
 
6.2%
t581666
 
6.0%
l552283
 
5.7%
h320643
 
3.3%
Other values (111)3174199
32.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)9660930
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
987386
 
10.2%
e754882
 
7.8%
o716244
 
7.4%
a705127
 
7.3%
r637989
 
6.6%
n629844
 
6.5%
i600667
 
6.2%
t581666
 
6.0%
l552283
 
5.7%
h320643
 
3.3%
Other values (111)3174199
32.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)9660930
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
987386
 
10.2%
e754882
 
7.8%
o716244
 
7.4%
a705127
 
7.3%
r637989
 
6.6%
n629844
 
6.5%
i600667
 
6.2%
t581666
 
6.0%
l552283
 
5.7%
h320643
 
3.3%
Other values (111)3174199
32.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)9660930
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
987386
 
10.2%
e754882
 
7.8%
o716244
 
7.4%
a705127
 
7.3%
r637989
 
6.6%
n629844
 
6.5%
i600667
 
6.2%
t581666
 
6.0%
l552283
 
5.7%
h320643
 
3.3%
Other values (111)3174199
32.9%

Dimensions
Text

Missing 

Distinct241145
Distinct (%)62.6%
Missing62843
Missing (%)14.0%
Memory size3.4 MiB
2025-10-24T01:14:36.632597image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2172
Median length1163
Mean length48.831264
Min length1

Characters and Unicode

Total characters18817616
Distinct characters128
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213991 ?
Unique (%)55.5%

Sample

1st rowDimensions unavailable
2nd rowDimensions unavailable
3rd rowDiam. 11/16 in. (1.7 cm)
4th rowDiam. 11/16 in. (1.7 cm)
5th rowDiam. 11/16 in. (1.7 cm)
ValueCountFrequency (%)
cm490531
 
10.2%
in487857
 
10.1%
x456834
 
9.5%
×270898
 
5.6%
sheet120680
 
2.5%
1/2107299
 
2.2%
292837
 
1.9%
3/479232
 
1.6%
174917
 
1.6%
1/474901
 
1.6%
Other values (19982)2568345
53.2%
2025-10-24T01:14:36.938960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4428634
23.5%
.1512148
 
8.0%
11377561
 
7.3%
/734918
 
3.9%
2654747
 
3.5%
i619747
 
3.3%
3608877
 
3.2%
m596067
 
3.2%
n562342
 
3.0%
c548853
 
2.9%
Other values (118)7173722
38.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)18817616
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4428634
23.5%
.1512148
 
8.0%
11377561
 
7.3%
/734918
 
3.9%
2654747
 
3.5%
i619747
 
3.3%
3608877
 
3.2%
m596067
 
3.2%
n562342
 
3.0%
c548853
 
2.9%
Other values (118)7173722
38.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)18817616
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4428634
23.5%
.1512148
 
8.0%
11377561
 
7.3%
/734918
 
3.9%
2654747
 
3.5%
i619747
 
3.3%
3608877
 
3.2%
m596067
 
3.2%
n562342
 
3.0%
c548853
 
2.9%
Other values (118)7173722
38.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)18817616
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4428634
23.5%
.1512148
 
8.0%
11377561
 
7.3%
/734918
 
3.9%
2654747
 
3.5%
i619747
 
3.3%
3608877
 
3.2%
m596067
 
3.2%
n562342
 
3.0%
c548853
 
2.9%
Other values (118)7173722
38.1%
Distinct37116
Distinct (%)8.3%
Missing670
Missing (%)0.1%
Memory size3.4 MiB
2025-10-24T01:14:37.176857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1142
Median length621
Mean length45.444685
Min length4

Characters and Unicode

Total characters20337996
Distinct characters143
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22290 ?
Unique (%)5.0%

Sample

1st rowGift of Heinz L. Stoppelmann, 1979
2nd rowGift of Heinz L. Stoppelmann, 1980
3rd rowGift of C. Ruxton Love, Jr., 1967
4th rowGift of C. Ruxton Love, Jr., 1967
5th rowGift of C. Ruxton Love, Jr., 1967
ValueCountFrequency (%)
of312105
 
9.4%
gift248646
 
7.5%
the163419
 
4.9%
collection125307
 
3.8%
fund123282
 
3.7%
r88842
 
2.7%
jefferson84232
 
2.5%
burdick83937
 
2.5%
rogers58703
 
1.8%
and58307
 
1.8%
Other values (17152)1981895
59.5%
2025-10-24T01:14:37.513472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2884050
 
14.2%
e1512570
 
7.4%
o1168059
 
5.7%
i1027178
 
5.1%
r1000616
 
4.9%
n902162
 
4.4%
t877255
 
4.3%
f788113
 
3.9%
s769517
 
3.8%
l702233
 
3.5%
Other values (133)8706243
42.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)20337996
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2884050
 
14.2%
e1512570
 
7.4%
o1168059
 
5.7%
i1027178
 
5.1%
r1000616
 
4.9%
n902162
 
4.4%
t877255
 
4.3%
f788113
 
3.9%
s769517
 
3.8%
l702233
 
3.5%
Other values (133)8706243
42.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)20337996
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2884050
 
14.2%
e1512570
 
7.4%
o1168059
 
5.7%
i1027178
 
5.1%
r1000616
 
4.9%
n902162
 
4.4%
t877255
 
4.3%
f788113
 
3.9%
s769517
 
3.8%
l702233
 
3.5%
Other values (133)8706243
42.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)20337996
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2884050
 
14.2%
e1512570
 
7.4%
o1168059
 
5.7%
i1027178
 
5.1%
r1000616
 
4.9%
n902162
 
4.4%
t877255
 
4.3%
f788113
 
3.9%
s769517
 
3.8%
l702233
 
3.5%
Other values (133)8706243
42.8%

Geography Type
Text

Missing 

Distinct125
Distinct (%)0.2%
Missing389740
Missing (%)87.0%
Memory size3.4 MiB
2025-10-24T01:14:37.616033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length72
Median length67
Mean length7.8007116
Min length1

Characters and Unicode

Total characters456053
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)0.1%

Sample

1st rowMade in
2nd rowMade in
3rd rowMade in
4th rowMade in
5th rowMade in
ValueCountFrequency (%)
from27935
29.5%
in20855
22.0%
made18049
19.1%
to8030
 
8.5%
attributed7779
 
8.2%
excavated3408
 
3.6%
probably1199
 
1.3%
possibly833
 
0.9%
from|probably644
 
0.7%
of620
 
0.7%
Other values (73)5313
 
5.6%
2025-10-24T01:14:37.795227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o43618
 
9.6%
r40995
 
9.0%
t36721
 
8.1%
36202
 
7.9%
i33738
 
7.4%
m31870
 
7.0%
e31597
 
6.9%
d31345
 
6.9%
a28900
 
6.3%
F28563
 
6.3%
Other values (25)112504
24.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)456053
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o43618
 
9.6%
r40995
 
9.0%
t36721
 
8.1%
36202
 
7.9%
i33738
 
7.4%
m31870
 
7.0%
e31597
 
6.9%
d31345
 
6.9%
a28900
 
6.3%
F28563
 
6.3%
Other values (25)112504
24.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)456053
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o43618
 
9.6%
r40995
 
9.0%
t36721
 
8.1%
36202
 
7.9%
i33738
 
7.4%
m31870
 
7.0%
e31597
 
6.9%
d31345
 
6.9%
a28900
 
6.3%
F28563
 
6.3%
Other values (25)112504
24.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)456053
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o43618
 
9.6%
r40995
 
9.0%
t36721
 
8.1%
36202
 
7.9%
i33738
 
7.4%
m31870
 
7.0%
e31597
 
6.9%
d31345
 
6.9%
a28900
 
6.3%
F28563
 
6.3%
Other values (25)112504
24.7%

City
Text

Missing 

Distinct2495
Distinct (%)8.2%
Missing417683
Missing (%)93.2%
Memory size3.4 MiB
2025-10-24T01:14:37.984018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length62
Median length49
Mean length8.144135
Min length2

Characters and Unicode

Total characters248559
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1504 ?
Unique (%)4.9%

Sample

1st rowPhiladelphia
2nd rowBristol
3rd rowNew York
4th rowLebanon
5th rowNorwich
ValueCountFrequency (%)
paris4569
 
12.1%
nishapur3720
 
9.9%
new2491
 
6.6%
york2364
 
6.3%
london1612
 
4.3%
venice821
 
2.2%
rome815
 
2.2%
probably706
 
1.9%
village584
 
1.5%
boston571
 
1.5%
Other values (2306)19459
51.6%
2025-10-24T01:14:38.256482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a23100
 
9.3%
r21581
 
8.7%
i19732
 
7.9%
e17932
 
7.2%
o16589
 
6.7%
s15417
 
6.2%
n14842
 
6.0%
h9040
 
3.6%
u8669
 
3.5%
l7624
 
3.1%
Other values (88)94033
37.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)248559
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a23100
 
9.3%
r21581
 
8.7%
i19732
 
7.9%
e17932
 
7.2%
o16589
 
6.7%
s15417
 
6.2%
n14842
 
6.0%
h9040
 
3.6%
u8669
 
3.5%
l7624
 
3.1%
Other values (88)94033
37.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)248559
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a23100
 
9.3%
r21581
 
8.7%
i19732
 
7.9%
e17932
 
7.2%
o16589
 
6.7%
s15417
 
6.2%
n14842
 
6.0%
h9040
 
3.6%
u8669
 
3.5%
l7624
 
3.1%
Other values (88)94033
37.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)248559
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a23100
 
9.3%
r21581
 
8.7%
i19732
 
7.9%
e17932
 
7.2%
o16589
 
6.7%
s15417
 
6.2%
n14842
 
6.0%
h9040
 
3.6%
u8669
 
3.5%
l7624
 
3.1%
Other values (88)94033
37.8%

State
Text

Missing 

Distinct1130
Distinct (%)13.5%
Missing439843
Missing (%)98.1%
Memory size3.4 MiB
2025-10-24T01:14:38.361686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length47
Median length42
Mean length12.257895
Min length2

Characters and Unicode

Total characters102476
Distinct characters86
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique650 ?
Unique (%)7.8%

Sample

1st rowStaffordshire
2nd rowStaffordshire
3rd rowStaffordshire
4th rowStaffordshire
5th rowStaffordshire
ValueCountFrequency (%)
province1037
 
7.0%
kharga888
 
6.0%
oasis888
 
6.0%
papua704
 
4.7%
irian699
 
4.7%
jaya698
 
4.7%
new585
 
3.9%
york429
 
2.9%
staffordshire290
 
1.9%
guerrero214
 
1.4%
Other values (908)8475
56.9%
2025-10-24T01:14:38.540311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a14108
 
13.8%
r8250
 
8.1%
i6672
 
6.5%
6555
 
6.4%
e6298
 
6.1%
n5767
 
5.6%
o5463
 
5.3%
s5178
 
5.1%
u3531
 
3.4%
t3008
 
2.9%
Other values (76)37646
36.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)102476
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a14108
 
13.8%
r8250
 
8.1%
i6672
 
6.5%
6555
 
6.4%
e6298
 
6.1%
n5767
 
5.6%
o5463
 
5.3%
s5178
 
5.1%
u3531
 
3.4%
t3008
 
2.9%
Other values (76)37646
36.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)102476
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a14108
 
13.8%
r8250
 
8.1%
i6672
 
6.5%
6555
 
6.4%
e6298
 
6.1%
n5767
 
5.6%
o5463
 
5.3%
s5178
 
5.1%
u3531
 
3.4%
t3008
 
2.9%
Other values (76)37646
36.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)102476
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a14108
 
13.8%
r8250
 
8.1%
i6672
 
6.5%
6555
 
6.4%
e6298
 
6.1%
n5767
 
5.6%
o5463
 
5.3%
s5178
 
5.1%
u3531
 
3.4%
t3008
 
2.9%
Other values (76)37646
36.7%

County
Text

Missing 

Distinct102
Distinct (%)4.1%
Missing445715
Missing (%)99.4%
Memory size3.4 MiB
2025-10-24T01:14:38.637513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length33
Median length1
Mean length4.8930868
Min length1

Characters and Unicode

Total characters12174
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)2.3%

Sample

1st rowStaffordshire
2nd rowStaffordshire
3rd rowStaffordshire
4th rowStaffordshire
5th rowStaffordshire
ValueCountFrequency (%)
1664
59.1%
staffordshire290
 
10.3%
county181
 
6.4%
west82
 
2.9%
yorkshire64
 
2.3%
queens49
 
1.7%
bristol49
 
1.7%
midlands43
 
1.5%
merseyside38
 
1.3%
brooklyn35
 
1.2%
Other values (102)322
 
11.4%
2025-10-24T01:14:38.825171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
|1836
15.1%
r1053
 
8.6%
e940
 
7.7%
s825
 
6.8%
o804
 
6.6%
t780
 
6.4%
f636
 
5.2%
i570
 
4.7%
a522
 
4.3%
n501
 
4.1%
Other values (42)3707
30.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)12174
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
|1836
15.1%
r1053
 
8.6%
e940
 
7.7%
s825
 
6.8%
o804
 
6.6%
t780
 
6.4%
f636
 
5.2%
i570
 
4.7%
a522
 
4.3%
n501
 
4.1%
Other values (42)3707
30.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)12174
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
|1836
15.1%
r1053
 
8.6%
e940
 
7.7%
s825
 
6.8%
o804
 
6.6%
t780
 
6.4%
f636
 
5.2%
i570
 
4.7%
a522
 
4.3%
n501
 
4.1%
Other values (42)3707
30.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)12174
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
|1836
15.1%
r1053
 
8.6%
e940
 
7.7%
s825
 
6.8%
o804
 
6.6%
t780
 
6.4%
f636
 
5.2%
i570
 
4.7%
a522
 
4.3%
n501
 
4.1%
Other values (42)3707
30.5%

Country
Text

Missing 

Distinct1035
Distinct (%)1.4%
Missing373753
Missing (%)83.4%
Memory size3.4 MiB
2025-10-24T01:14:38.989920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length70
Median length61
Mean length7.5262727
Min length2

Characters and Unicode

Total characters560331
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique532 ?
Unique (%)0.7%

Sample

1st rowMexico
2nd rowMexico
3rd rowMexico
4th rowMexico
5th rowMexico
ValueCountFrequency (%)
egypt33153
34.5%
united9259
 
9.6%
states8897
 
9.3%
iran6214
 
6.5%
peru3451
 
3.6%
france2111
 
2.2%
byzantine1675
 
1.7%
india1581
 
1.6%
mexico1579
 
1.6%
indonesia1397
 
1.5%
Other values (580)26821
27.9%
2025-10-24T01:14:39.245464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t68177
12.2%
a44597
 
8.0%
e41573
 
7.4%
y39654
 
7.1%
n38818
 
6.9%
p36918
 
6.6%
g36875
 
6.6%
E34953
 
6.2%
i27667
 
4.9%
r23508
 
4.2%
Other values (62)167591
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)560331
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t68177
12.2%
a44597
 
8.0%
e41573
 
7.4%
y39654
 
7.1%
n38818
 
6.9%
p36918
 
6.6%
g36875
 
6.6%
E34953
 
6.2%
i27667
 
4.9%
r23508
 
4.2%
Other values (62)167591
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)560331
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t68177
12.2%
a44597
 
8.0%
e41573
 
7.4%
y39654
 
7.1%
n38818
 
6.9%
p36918
 
6.6%
g36875
 
6.6%
E34953
 
6.2%
i27667
 
4.9%
r23508
 
4.2%
Other values (62)167591
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)560331
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t68177
12.2%
a44597
 
8.0%
e41573
 
7.4%
y39654
 
7.1%
n38818
 
6.9%
p36918
 
6.6%
g36875
 
6.6%
E34953
 
6.2%
i27667
 
4.9%
r23508
 
4.2%
Other values (62)167591
29.9%

Region
Text

Missing 

Distinct705
Distinct (%)2.3%
Missing417125
Missing (%)93.1%
Memory size3.4 MiB
2025-10-24T01:14:39.386325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length48
Median length47
Mean length15.054926
Min length3

Characters and Unicode

Total characters467877
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique351 ?
Unique (%)1.1%

Sample

1st rowNew England
2nd rowNew England
3rd rowNew England
4th rowNew England
5th rowNew England
ValueCountFrequency (%)
egypt13544
19.6%
upper12262
17.8%
thebes11171
16.2%
region5114
 
7.4%
memphite4677
 
6.8%
iran2553
 
3.7%
mesopotamia2349
 
3.4%
middle1288
 
1.9%
mesoamerica1281
 
1.9%
northern1078
 
1.6%
Other values (523)13708
19.9%
2025-10-24T01:14:39.559728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e63732
 
13.6%
p45540
 
9.7%
38355
 
8.2%
t28018
 
6.0%
r25795
 
5.5%
a22072
 
4.7%
i19772
 
4.2%
s19743
 
4.2%
g19486
 
4.2%
h18218
 
3.9%
Other values (57)167146
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)467877
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e63732
 
13.6%
p45540
 
9.7%
38355
 
8.2%
t28018
 
6.0%
r25795
 
5.5%
a22072
 
4.7%
i19772
 
4.2%
s19743
 
4.2%
g19486
 
4.2%
h18218
 
3.9%
Other values (57)167146
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)467877
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e63732
 
13.6%
p45540
 
9.7%
38355
 
8.2%
t28018
 
6.0%
r25795
 
5.5%
a22072
 
4.7%
i19772
 
4.2%
s19743
 
4.2%
g19486
 
4.2%
h18218
 
3.9%
Other values (57)167146
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)467877
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e63732
 
13.6%
p45540
 
9.7%
38355
 
8.2%
t28018
 
6.0%
r25795
 
5.5%
a22072
 
4.7%
i19772
 
4.2%
s19743
 
4.2%
g19486
 
4.2%
h18218
 
3.9%
Other values (57)167146
35.7%

Subregion
Text

Missing 

Distinct361
Distinct (%)1.7%
Missing426487
Missing (%)95.2%
Memory size3.4 MiB
2025-10-24T01:14:39.680632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length50
Median length42
Mean length13.14487
Min length3

Characters and Unicode

Total characters285454
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)0.6%

Sample

1st rowBabylon (?) (modern Hillah)
2nd rowBabylon (?) (modern Hillah)
3rd rowBabylon (modern Hillah)
4th rowBabylon (modern Hillah)
5th rowBabylon (modern Hillah)
ValueCountFrequency (%)
lisht3918
 
9.0%
deir3225
 
7.4%
el-bahri3063
 
7.0%
north3011
 
6.9%
asasif2951
 
6.8%
malqata2166
 
5.0%
southern1409
 
3.2%
south912
 
2.1%
akhetaten857
 
2.0%
amarna837
 
1.9%
Other values (439)21366
48.9%
2025-10-24T01:14:39.895727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a29471
 
10.3%
22529
 
7.9%
i21300
 
7.5%
e19575
 
6.9%
r19396
 
6.8%
h18435
 
6.5%
t16571
 
5.8%
s16375
 
5.7%
l12316
 
4.3%
o10368
 
3.6%
Other values (62)99118
34.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)285454
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a29471
 
10.3%
22529
 
7.9%
i21300
 
7.5%
e19575
 
6.9%
r19396
 
6.8%
h18435
 
6.5%
t16571
 
5.8%
s16375
 
5.7%
l12316
 
4.3%
o10368
 
3.6%
Other values (62)99118
34.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)285454
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a29471
 
10.3%
22529
 
7.9%
i21300
 
7.5%
e19575
 
6.9%
r19396
 
6.8%
h18435
 
6.5%
t16571
 
5.8%
s16375
 
5.7%
l12316
 
4.3%
o10368
 
3.6%
Other values (62)99118
34.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)285454
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a29471
 
10.3%
22529
 
7.9%
i21300
 
7.5%
e19575
 
6.9%
r19396
 
6.8%
h18435
 
6.5%
t16571
 
5.8%
s16375
 
5.7%
l12316
 
4.3%
o10368
 
3.6%
Other values (62)99118
34.7%

Locale
Text

Missing 

Distinct818
Distinct (%)5.4%
Missing433108
Missing (%)96.6%
Memory size3.4 MiB
2025-10-24T01:14:40.031172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length68
Median length59
Mean length22.473667
Min length2

Characters and Unicode

Total characters339240
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique372 ?
Unique (%)2.5%

Sample

1st rowMastaba of Imhotep
2nd rowprobably Tomb CC 64, burial 9
3rd rowpit tomb CC 25
4th rowTomb of Hatnefer and Ramose (below TT 71)
5th rowPyramid complex of Pepi II probably
ValueCountFrequency (%)
of10113
 
15.9%
tomb6131
 
9.7%
mma3502
 
5.5%
cemetery2866
 
4.5%
tt2614
 
4.1%
palace2009
 
3.2%
temple1924
 
3.0%
iii1849
 
2.9%
amenhotep1579
 
2.5%
the1238
 
1.9%
Other values (746)29692
46.7%
2025-10-24T01:14:40.328001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48446
 
14.3%
e36174
 
10.7%
o23861
 
7.0%
m17159
 
5.1%
t16456
 
4.9%
a13894
 
4.1%
T13716
 
4.0%
f10879
 
3.2%
r10132
 
3.0%
s9726
 
2.9%
Other values (67)138797
40.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)339240
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
48446
 
14.3%
e36174
 
10.7%
o23861
 
7.0%
m17159
 
5.1%
t16456
 
4.9%
a13894
 
4.1%
T13716
 
4.0%
f10879
 
3.2%
r10132
 
3.0%
s9726
 
2.9%
Other values (67)138797
40.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)339240
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
48446
 
14.3%
e36174
 
10.7%
o23861
 
7.0%
m17159
 
5.1%
t16456
 
4.9%
a13894
 
4.1%
T13716
 
4.0%
f10879
 
3.2%
r10132
 
3.0%
s9726
 
2.9%
Other values (67)138797
40.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)339240
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
48446
 
14.3%
e36174
 
10.7%
o23861
 
7.0%
m17159
 
5.1%
t16456
 
4.9%
a13894
 
4.1%
T13716
 
4.0%
f10879
 
3.2%
r10132
 
3.0%
s9726
 
2.9%
Other values (67)138797
40.9%

Locus
Text

Missing 

Distinct1324
Distinct (%)19.1%
Missing441264
Missing (%)98.5%
Memory size3.4 MiB
2025-10-24T01:14:40.461858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length48
Median length40
Mean length19.422827
Min length1

Characters and Unicode

Total characters134775
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique743 ?
Unique (%)10.7%

Sample

1st rowchamber inside the south enclosure wall
2nd rowdebris
3rd rowoutside entrance
4th rowTomb of Kaemsenu, west wall of cult chapel
5th rowKaemsenu tomb probably
ValueCountFrequency (%)
of1299
 
5.5%
pit1285
 
5.4%
burial1198
 
5.0%
chamber862
 
3.6%
deposit811
 
3.4%
foundation701
 
3.0%
wall626
 
2.6%
b624
 
2.6%
tomb582
 
2.5%
4505
 
2.1%
Other values (1059)15234
64.2%
2025-10-24T01:14:40.648722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16793
 
12.5%
o9376
 
7.0%
e9183
 
6.8%
t8754
 
6.5%
i8019
 
5.9%
a7947
 
5.9%
r7692
 
5.7%
n5816
 
4.3%
u4307
 
3.2%
s4201
 
3.1%
Other values (69)52687
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)134775
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
16793
 
12.5%
o9376
 
7.0%
e9183
 
6.8%
t8754
 
6.5%
i8019
 
5.9%
a7947
 
5.9%
r7692
 
5.7%
n5816
 
4.3%
u4307
 
3.2%
s4201
 
3.1%
Other values (69)52687
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)134775
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
16793
 
12.5%
o9376
 
7.0%
e9183
 
6.8%
t8754
 
6.5%
i8019
 
5.9%
a7947
 
5.9%
r7692
 
5.7%
n5816
 
4.3%
u4307
 
3.2%
s4201
 
3.1%
Other values (69)52687
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)134775
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
16793
 
12.5%
o9376
 
7.0%
e9183
 
6.8%
t8754
 
6.5%
i8019
 
5.9%
a7947
 
5.9%
r7692
 
5.7%
n5816
 
4.3%
u4307
 
3.2%
s4201
 
3.1%
Other values (69)52687
39.1%

Excavation
Text

Missing 

Distinct331
Distinct (%)2.1%
Missing432684
Missing (%)96.5%
Memory size3.4 MiB
2025-10-24T01:14:40.788760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length24
Mean length24.160964
Min length3

Characters and Unicode

Total characters374954
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique123 ?
Unique (%)0.8%

Sample

1st rowMMA excavations, 1913–14
2nd rowCarnarvon Excavations 1907–1914
3rd rowCarnarvon/Carter excavations, 1910
4th rowMMA excavations, 1935–36
5th rowEgyptian Antiquities Service excavations
ValueCountFrequency (%)
excavations15422
33.6%
mma12155
26.5%
19201287
 
2.8%
1920–221152
 
2.5%
1923–24780
 
1.7%
1913–14774
 
1.7%
1922–23686
 
1.5%
1915–16677
 
1.5%
1891–92670
 
1.5%
petrie/carter647
 
1.4%
Other values (273)11684
25.4%
2025-10-24T01:14:41.094421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a34823
 
9.3%
30428
 
8.1%
M24467
 
6.5%
122001
 
5.9%
t19213
 
5.1%
e19074
 
5.1%
i19049
 
5.1%
n18230
 
4.9%
o17634
 
4.7%
v16746
 
4.5%
Other values (62)153289
40.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)374954
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a34823
 
9.3%
30428
 
8.1%
M24467
 
6.5%
122001
 
5.9%
t19213
 
5.1%
e19074
 
5.1%
i19049
 
5.1%
n18230
 
4.9%
o17634
 
4.7%
v16746
 
4.5%
Other values (62)153289
40.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)374954
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a34823
 
9.3%
30428
 
8.1%
M24467
 
6.5%
122001
 
5.9%
t19213
 
5.1%
e19074
 
5.1%
i19049
 
5.1%
n18230
 
4.9%
o17634
 
4.7%
v16746
 
4.5%
Other values (62)153289
40.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)374954
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a34823
 
9.3%
30428
 
8.1%
M24467
 
6.5%
122001
 
5.9%
t19213
 
5.1%
e19074
 
5.1%
i19049
 
5.1%
n18230
 
4.9%
o17634
 
4.7%
v16746
 
4.5%
Other values (62)153289
40.9%

River
Text

Missing 

Distinct231
Distinct (%)11.0%
Missing446100
Missing (%)99.5%
Memory size3.4 MiB
2025-10-24T01:14:41.252968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length42
Median length38
Mean length18.743224
Min length7

Characters and Unicode

Total characters39417
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)4.4%

Sample

1st rowAtrato River
2nd rowAtrato River
3rd rowAtrato River
4th rowAtrato River
5th rowAtrato River
ValueCountFrequency (%)
river1755
27.2%
region856
13.2%
sepik636
 
9.8%
upper423
 
6.5%
middle185
 
2.9%
balsas180
 
2.8%
rio122
 
1.9%
pomatsj109
 
1.7%
sankuru99
 
1.5%
bay98
 
1.5%
Other values (168)2000
30.9%
2025-10-24T01:14:41.519398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e4865
12.3%
4368
 
11.1%
i4247
 
10.8%
r4160
 
10.6%
a2100
 
5.3%
R1910
 
4.8%
v1790
 
4.5%
n1765
 
4.5%
o1644
 
4.2%
p1540
 
3.9%
Other values (51)11028
28.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)39417
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e4865
12.3%
4368
 
11.1%
i4247
 
10.8%
r4160
 
10.6%
a2100
 
5.3%
R1910
 
4.8%
v1790
 
4.5%
n1765
 
4.5%
o1644
 
4.2%
p1540
 
3.9%
Other values (51)11028
28.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)39417
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e4865
12.3%
4368
 
11.1%
i4247
 
10.8%
r4160
 
10.6%
a2100
 
5.3%
R1910
 
4.8%
v1790
 
4.5%
n1765
 
4.5%
o1644
 
4.2%
p1540
 
3.9%
Other values (51)11028
28.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)39417
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e4865
12.3%
4368
 
11.1%
i4247
 
10.8%
r4160
 
10.6%
a2100
 
5.3%
R1910
 
4.8%
v1790
 
4.5%
n1765
 
4.5%
o1644
 
4.2%
p1540
 
3.9%
Other values (51)11028
28.0%

Classification
Text

Missing 

Distinct1077
Distinct (%)0.3%
Missing58279
Missing (%)13.0%
Memory size3.4 MiB
2025-10-24T01:14:41.654316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length74
Median length65
Mean length12.115769
Min length1

Characters and Unicode

Total characters4724229
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)0.1%

Sample

1st rowMetal
2nd rowMetal
3rd rowMetal
4th rowMetal
5th rowMetal
ValueCountFrequency (%)
prints69260
 
15.0%
prints|ephemera30033
 
6.5%
photographs26821
 
5.8%
drawings25230
 
5.5%
20415
 
4.4%
books15461
 
3.4%
architecture14748
 
3.2%
ceramics13332
 
2.9%
paintings11041
 
2.4%
textiles-woven10995
 
2.4%
Other values (1124)223417
48.5%
2025-10-24T01:14:41.859119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e448409
 
9.5%
r439208
 
9.3%
s405201
 
8.6%
t362415
 
7.7%
i317488
 
6.7%
n291206
 
6.2%
a284846
 
6.0%
o244327
 
5.2%
P183319
 
3.9%
h152388
 
3.2%
Other values (61)1595422
33.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)4724229
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e448409
 
9.5%
r439208
 
9.3%
s405201
 
8.6%
t362415
 
7.7%
i317488
 
6.7%
n291206
 
6.2%
a284846
 
6.0%
o244327
 
5.2%
P183319
 
3.9%
h152388
 
3.2%
Other values (61)1595422
33.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4724229
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e448409
 
9.5%
r439208
 
9.3%
s405201
 
8.6%
t362415
 
7.7%
i317488
 
6.7%
n291206
 
6.2%
a284846
 
6.0%
o244327
 
5.2%
P183319
 
3.9%
h152388
 
3.2%
Other values (61)1595422
33.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4724229
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e448409
 
9.5%
r439208
 
9.3%
s405201
 
8.6%
t362415
 
7.7%
i317488
 
6.7%
n291206
 
6.2%
a284846
 
6.0%
o244327
 
5.2%
P183319
 
3.9%
h152388
 
3.2%
Other values (61)1595422
33.8%
Distinct1146
Distinct (%)5.0%
Missing425228
Missing (%)94.9%
Memory size3.4 MiB
2025-10-24T01:14:41.939939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length216
Median length183
Mean length46.023025
Min length1

Characters and Unicode

Total characters1057379
Distinct characters104
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique627 ?
Unique (%)2.7%

Sample

1st row© 2017 Artists Rights Society (ARS), New York
2nd row© 2017 Artists Rights Society (ARS), New York
3rd row© 2017 Artists Rights Society (ARS), New York
4th row© 2017 Artists Rights Society (ARS), New York
5th row© 2017 Artists Rights Society (ARS), New York
ValueCountFrequency (%)
©22404
 
12.4%
of11444
 
6.3%
the10634
 
5.9%
museum9715
 
5.4%
archive9615
 
5.3%
art9570
 
5.3%
walker9531
 
5.3%
evans9524
 
5.3%
metropolitan9523
 
5.3%
rights7617
 
4.2%
Other values (1876)71397
39.5%
2025-10-24T01:14:42.113772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158044
 
14.9%
e81177
 
7.7%
t68708
 
6.5%
r64618
 
6.1%
o55053
 
5.2%
s51450
 
4.9%
i49813
 
4.7%
a41041
 
3.9%
A36073
 
3.4%
h32924
 
3.1%
Other values (94)418478
39.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)1057379
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
158044
 
14.9%
e81177
 
7.7%
t68708
 
6.5%
r64618
 
6.1%
o55053
 
5.2%
s51450
 
4.9%
i49813
 
4.7%
a41041
 
3.9%
A36073
 
3.4%
h32924
 
3.1%
Other values (94)418478
39.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1057379
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
158044
 
14.9%
e81177
 
7.7%
t68708
 
6.5%
r64618
 
6.1%
o55053
 
5.2%
s51450
 
4.9%
i49813
 
4.7%
a41041
 
3.9%
A36073
 
3.4%
h32924
 
3.1%
Other values (94)418478
39.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1057379
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
158044
 
14.9%
e81177
 
7.7%
t68708
 
6.5%
r64618
 
6.1%
o55053
 
5.2%
s51450
 
4.9%
i49813
 
4.7%
a41041
 
3.9%
A36073
 
3.4%
h32924
 
3.1%
Other values (94)418478
39.6%

Link Resource
Text

Unique 

Distinct448203
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
2025-10-24T01:14:42.505459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length53
Median length53
Mean length52.802953
Min length48

Characters and Unicode

Total characters23666442
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique448203 ?
Unique (%)100.0%

Sample

1st rowhttp://www.metmuseum.org/art/collection/search/1
2nd rowhttp://www.metmuseum.org/art/collection/search/2
3rd rowhttp://www.metmuseum.org/art/collection/search/3
4th rowhttp://www.metmuseum.org/art/collection/search/4
5th rowhttp://www.metmuseum.org/art/collection/search/5
ValueCountFrequency (%)
http://www.metmuseum.org/art/collection/search/121
 
< 0.1%
http://www.metmuseum.org/art/collection/search/7508301
 
< 0.1%
http://www.metmuseum.org/art/collection/search/11
 
< 0.1%
http://www.metmuseum.org/art/collection/search/21
 
< 0.1%
http://www.metmuseum.org/art/collection/search/31
 
< 0.1%
http://www.metmuseum.org/art/collection/search/41
 
< 0.1%
http://www.metmuseum.org/art/collection/search/51
 
< 0.1%
http://www.metmuseum.org/art/collection/search/61
 
< 0.1%
http://www.metmuseum.org/art/collection/search/71
 
< 0.1%
http://www.metmuseum.org/art/collection/search/81
 
< 0.1%
Other values (448193)448193
> 99.9%
2025-10-24T01:14:42.963539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/2689218
 
11.4%
t2241015
 
9.5%
e1792812
 
7.6%
w1344609
 
5.7%
m1344609
 
5.7%
o1344609
 
5.7%
r1344609
 
5.7%
c1344609
 
5.7%
h896406
 
3.8%
s896406
 
3.8%
Other values (19)8427540
35.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)23666442
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/2689218
 
11.4%
t2241015
 
9.5%
e1792812
 
7.6%
w1344609
 
5.7%
m1344609
 
5.7%
o1344609
 
5.7%
r1344609
 
5.7%
c1344609
 
5.7%
h896406
 
3.8%
s896406
 
3.8%
Other values (19)8427540
35.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)23666442
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/2689218
 
11.4%
t2241015
 
9.5%
e1792812
 
7.6%
w1344609
 
5.7%
m1344609
 
5.7%
o1344609
 
5.7%
r1344609
 
5.7%
c1344609
 
5.7%
h896406
 
3.8%
s896406
 
3.8%
Other values (19)8427540
35.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)23666442
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/2689218
 
11.4%
t2241015
 
9.5%
e1792812
 
7.6%
w1344609
 
5.7%
m1344609
 
5.7%
o1344609
 
5.7%
r1344609
 
5.7%
c1344609
 
5.7%
h896406
 
3.8%
s896406
 
3.8%
Other values (19)8427540
35.6%

Metadata Date
Date

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
Minimum2017-04-03 08:00:08
Maximum2017-04-03 08:00:08
Invalid dates0
Invalid dates (%)0.0%
2025-10-24T01:14:43.020163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:43.073664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Repository
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.4 MiB
Metropolitan Museum of Art, New York, NY
448203 

Length

Max length40
Median length40
Mean length40
Min length40

Characters and Unicode

Total characters17928120
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMetropolitan Museum of Art, New York, NY
2nd rowMetropolitan Museum of Art, New York, NY
3rd rowMetropolitan Museum of Art, New York, NY
4th rowMetropolitan Museum of Art, New York, NY
5th rowMetropolitan Museum of Art, New York, NY

Common Values

ValueCountFrequency (%)
Metropolitan Museum of Art, New York, NY448203
100.0%

Length

2025-10-24T01:14:43.138149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-24T01:14:43.178963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
metropolitan448203
14.3%
museum448203
14.3%
of448203
14.3%
art448203
14.3%
new448203
14.3%
york448203
14.3%
ny448203
14.3%

Most occurring characters

ValueCountFrequency (%)
2689218
15.0%
o1792812
 
10.0%
t1344609
 
7.5%
r1344609
 
7.5%
e1344609
 
7.5%
M896406
 
5.0%
u896406
 
5.0%
N896406
 
5.0%
,896406
 
5.0%
Y896406
 
5.0%
Other values (11)4930233
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)17928120
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2689218
15.0%
o1792812
 
10.0%
t1344609
 
7.5%
r1344609
 
7.5%
e1344609
 
7.5%
M896406
 
5.0%
u896406
 
5.0%
N896406
 
5.0%
,896406
 
5.0%
Y896406
 
5.0%
Other values (11)4930233
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)17928120
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2689218
15.0%
o1792812
 
10.0%
t1344609
 
7.5%
r1344609
 
7.5%
e1344609
 
7.5%
M896406
 
5.0%
u896406
 
5.0%
N896406
 
5.0%
,896406
 
5.0%
Y896406
 
5.0%
Other values (11)4930233
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)17928120
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2689218
15.0%
o1792812
 
10.0%
t1344609
 
7.5%
r1344609
 
7.5%
e1344609
 
7.5%
M896406
 
5.0%
u896406
 
5.0%
N896406
 
5.0%
,896406
 
5.0%
Y896406
 
5.0%
Other values (11)4930233
27.5%

Interactions

2025-10-24T01:14:20.063856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:19.414111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:19.739055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:20.166408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:19.528256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:19.844624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:20.264827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:19.630766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-24T01:14:19.961413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-10-24T01:14:43.214203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
DepartmentIs HighlightIs Public DomainObject Begin DateObject End DateObject ID
Department1.0000.3000.5090.0000.0000.757
Is Highlight0.3001.0000.0450.0000.0000.051
Is Public Domain0.5090.0451.0000.0000.0000.335
Object Begin Date0.0000.0000.0001.0000.9340.013
Object End Date0.0000.0000.0000.9341.000-0.076
Object ID0.7570.0510.3350.013-0.0761.000

Missing values

2025-10-24T01:14:20.604686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-24T01:14:21.577652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-10-24T01:14:25.452926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Object NumberIs HighlightIs Public DomainObject IDDepartmentObject NameTitleCulturePeriodDynastyReignPortfolioArtist RoleArtist PrefixArtist Display NameArtist Display BioArtist SuffixArtist Alpha SortArtist NationalityArtist Begin DateArtist End DateObject DateObject Begin DateObject End DateMediumDimensionsCredit LineGeography TypeCityStateCountyCountryRegionSubregionLocaleLocusExcavationRiverClassificationRights and ReproductionLink ResourceMetadata DateRepository
01979.486.1FalseFalse1American Decorative ArtsCoinOne-dollar Liberty Head CoinNaNNaNNaNNaNNaNMakerNaNJames Barton LongacreAmerican, Delaware County, Pennsylvania 1794–1869 Philadelphia, PennsylvaniaNaNLongacre, James BartonAmerican17941869185318531853GoldDimensions unavailableGift of Heinz L. Stoppelmann, 1979NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/14/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
11980.264.5FalseFalse2American Decorative ArtsCoinTen-dollar Liberty Head CoinNaNNaNNaNNaNNaNMakerNaNChristian Gobrecht1785–1844NaNGobrecht, ChristianNaN17851844190119011901GoldDimensions unavailableGift of Heinz L. Stoppelmann, 1980NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/24/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
267.265.9FalseFalse3American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/34/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
367.265.10FalseFalse4American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/44/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
467.265.11FalseFalse5American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/54/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
567.265.12FalseFalse6American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/64/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
667.265.13FalseFalse7American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/74/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
767.265.14FalseFalse8American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/84/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
867.265.15FalseFalse9American Decorative ArtsCoinTwo-and-a-Half Dollar CoinNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN1909–2719091927GoldDiam. 11/16 in. (1.7 cm)Gift of C. Ruxton Love, Jr., 1967NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/94/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
91979.486.3FalseFalse10American Decorative ArtsCoinTwo-and-a-half-dollar Indian Head CoinNaNNaNNaNNaNNaNMakerNaNBela Lyon Pratt1867–1917NaNPratt, Bela LyonNaN18671917191219121912GoldDimensions unavailableGift of Heinz L. Stoppelmann, 1979NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMetalNaNhttp://www.metmuseum.org/art/collection/search/104/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
Object NumberIs HighlightIs Public DomainObject IDDepartmentObject NameTitleCulturePeriodDynastyReignPortfolioArtist RoleArtist PrefixArtist Display NameArtist Display BioArtist SuffixArtist Alpha SortArtist NationalityArtist Begin DateArtist End DateObject DateObject Begin DateObject End DateMediumDimensionsCredit LineGeography TypeCityStateCountyCountryRegionSubregionLocaleLocusExcavationRiverClassificationRights and ReproductionLink ResourceMetadata DateRepository
4481931994.338.1FalseFalse750821Drawings and PrintsPrintThe Madonna and Child Seated on the CloudsNaNNaNNaNNaNNaNArtist|ArtistAfterParmigianino (Girolamo Francesco Maria Mazzola)|Anton Maria Zanetti the ElderItalian, Parma 1503–1540 Casalmaggiore|Italian, Venice 1680–1767 VeniceNaNParmigianino (Girolamo Francesco Maria Mazzola)|Zanetti, Anton Maria, the ElderNaN1503 |16801540 |1767172317231723Chiaroscuro woodcut from three blocks6 9/16 × 3 5/8 in. (16.7 × 9.2 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508214/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4481941994.338.2FalseFalse750822Drawings and PrintsPrintVertumnus and Pomona (Portrait of Anne Varice de Valliere)NaNNaNNaNNaNNaNArtist|EngraverAfterHyacinthe Rigaud|Michel DossierFrench, Perpignan 1659–1743 Paris|French, 1684–1750NaNRigaud, Hyacinthe|Dossier, MichelNaN1659 |16841743 |1750ca. 170917041714Engraving18 1/2 × 13 5/8 in. (47 × 34.6 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508224/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4481951994.338.4FalseFalse750823Drawings and PrintsPrintPhilippus Ludovicus, Comes a SinzendorfNaNNaNNaNNaNNaNArtistAfterHyacinthe RigaudFrench, Perpignan 1659–1743 ParisNaNRigaud, HyacintheNaN16591743ca. 172017151725Engraving20 1/2 × 15 1/2 in. (52.1 × 39.4 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508234/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4481961994.338.5FalseFalse750824Drawings and PrintsPrintGuillaume Cardinal DuboisNaNNaNNaNNaNNaNArtistAfterHyacinthe RigaudFrench, Perpignan 1659–1743 ParisNaNRigaud, HyacintheNaN16591743ca. 172017151725Engraving19 3/4 × 14 3/4 in. (50.2 × 37.5 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508244/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4481971994.338.8FalseFalse750825Drawings and PrintsPrintDon Ferdinande de Toledo, Duke of AlbaNaNNaNNaNNaNNaNArtistNaNAnonymous, Dutch, 17th centuryNaNNaNAnonymous, Dutch, 17th centuryNaN16001700ca. 160015951605Engraving8 1/8 × 6 1/2 in. (20.6 × 16.5 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508254/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4481981994.338.10FalseFalse750826Drawings and PrintsPrintEric, King of SwedenNaNNaNNaNNaNNaNArtistNaNFrans HuysNetherlandish, 1522–1562NaNHuys, FransNaN15221562ca. 155015451555Engraving9 1/8 in. × 7 in. (23.2 × 17.8 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508264/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4481991994.338.12FalseFalse750827Drawings and PrintsPrintLouis XIII of FranceNaNNaNNaNNaNNaNArtistNaNCrispijn de Passe the YoungerDutch, Cologne ca. 1594–1670 AmsterdamNaNPasse, Crispijn de, the YoungerNaN15901670162416241624Engraving11 1/2 × 8 3/4 in. (29.2 × 22.2 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508274/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4482001994.338.15FalseFalse750828Drawings and PrintsPrintGeorge RemNaNNaNNaNNaNNaNArtistNaNPeter IsselburgGerman, 1568–1626NaNIsselburg, PeterNaN15681626ca. 160015951605Engraving7 in. × 4 1/2 in. (17.8 × 11.4 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508284/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4482011994.338.16FalseFalse750829Drawings and PrintsPrintHenry de la Tour d'AuvergneNaNNaNNaNNaNNaNEngraver|ArtistAfterNicolas de Larmessin|Juste Aurèle MeissonnierFrench, Paris 1685–1755 Paris|French, Turin 1695–1750 ParisNaNLarmessin, Nicolas de|Meissonnier, Juste-AurèleNaN1685 |16951755 |1750ca. 172017151725Engraving10 3/8 × 7 3/4 in. (26.4 × 19.7 cm)Gift of Herbert Mitchell, 1994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508294/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY
4482021986.1180.500FalseFalse750830Drawings and PrintsPrintMr. Necker, Ministre d'Etat et Directeur Général des FinancesNaNNaNNaNNaNNaNArtistNaNPierre AudouinFrench, Paris 1768–1822 ParisNaNAudouin, PierreNaN17681822NaN17881822EngravingPlate: 5 3/4 x 7 3/4 in. (14.6 x 19.7cm)Bequest of Grace M. Pugh, 1985NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNPrintsNaNhttp://www.metmuseum.org/art/collection/search/7508304/3/2017 8:00:08 AMMetropolitan Museum of Art, New York, NY